Data science fundamentals for Python and Mongodb
Material type: TextPublication details: Apress Media 2018 New YorkDescription: xiii, 214 p.: ill. Includes indexISBN:- 9781484240182
- 006.312 P2D2
Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
---|---|---|---|---|---|---|---|---|
Book | Ahmedabad General Stacks | Non-fiction | 006.312 P2D2 (Browse shelf(Opens below)) | Available | 201179 |
Browsing Ahmedabad shelves, Shelving location: General Stacks, Collection: Non-fiction Close shelf browser (Hides shelf browser)
006.312 K9T3 Text mining in practice with R | 006.312 L4S3-2020 Sentiment analysis: mining opinions, sentiments, and emotions | 006.312 M6M2 Machine learning: algorithms and applications | 006.312 P2D2 Data science fundamentals for Python and Mongodb | 006.312 P3E9 Exploratory data analysis using R | 006.312 R6A2 Advanced data science and analytics with Python | 006.312 R6D2 Data science and analytics with python |
Table of Contents
1. Introduction
2. Monte Carlo Simulation and Density Functions
3. Linear Algebra
4. Gradient Descent
5. Working with Data
6. Exploring Data
Build the foundational data science skills necessary to work with and better understand complex data science algorithms. This example-driven book provides complete Python coding examples to complement and clarify data science concepts, and enrich the learning experience. Coding examples include visualizations whenever appropriate. The book is a necessary precursor to applying and implementing machine learning algorithms.
The book is self-contained. All of the math, statistics, stochastic, and programming skills required to master the content are covered. In-depth knowledge of object-oriented programming isn’t required because complete examples are provided and explained.
Data Science Fundamentals with Python and MongoDB is an excellent starting point for those interested in pursuing a career in data science. Like any science, the fundamentals of data science are a prerequisite to competency. Without proficiency in mathematics, statistics, data manipulation, and coding, the path to success is “rocky” at best. The coding examples in this book are concise, accurate, and complete, and perfectly complement the data science concepts introduced.
What You'll Learn
Prepare for a career in data science
Work with complex data structures in Python
Simulate with Monte Carlo and Stochastic algorithms
Apply linear algebra using vectors and matrices
Utilize complex algorithms such as gradient descent and principal component analysis
Wrangle, cleanse, visualize, and problem solve with data
Use MongoDB and JSON to work with data
Who This Book Is For
The novice yearning to break into the data science world, and the enthusiast looking to enrich, deepen, and develop data science skills through mastering the underlying fundamentals that are sometimes skipped over in the rush to be productive. Some knowledge of object-oriented programming will make learning easier.
https://www.apress.com/gp/book/9781484235966
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